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The idea of predicting offset instead of pixel-wise probability is wide-applied recently (e.g., "Dense 3D Regression for Hand Pose Estimation", "AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation", "Point-to-Point Regression PointNet for 3D Hand Pose Estimation").
In my opinion, predicting offset makes the output joints more accurate.
Sorry I don't understand your question very clearly. We use center point and bndbox to crop the hand/human-centered sub-image, mean/std normalize the original data.
@zhangboshen
I understand the first question, the second question I read the relevant code, also understand, thank you very much, and I love you this article! Thank you again!
Thank you very much for your excellent code, but I would like to ask you a few questions:
What are the specific functions of GT key point documents?
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